Method and system for analyzing a plurality of parts

ABSTRACT

The present invention includes a method and system configured to analyze a plurality of parts, each of the parts having at least one part characteristic. The method includes the steps of establishing at least one repository of the part characteristics, establishing a relationship between at least a portion of the parts and a cost characteristic; and, analyzing the portion of the parts in response to the relationship.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is based on and claims the benefit of U.S.Non-Provisional patent application Ser. No. 10/328,071, filed on Dec.23, 2002 and entitled “A Method and System for Analyzing a Plurality ofParts” which is incorporated herein by reference in its entirety.

TECHNICAL FIELD

This invention relates generally to a method and system configured toanalyze a plurality of parts, and more particularly, to a method andsystem configured to establish a relationship between at least a portionof the parts and a cost characteristic.

BACKGROUND

Many companies operate in an extremely cost conscious environment. Inmany cases product markets will not support an increase in the price ofthe products, despite the pressures from economic factors such asinflation, to raise the prices. Therefore companies are looking withinto determine how to reduce the cost of manufacturing the products. Acompany may increase their profit associated with a product by reducingthe cost of manufacturing the product, as opposed to raising the priceof the product. One such cost reduction process has been to manuallyreview the parts, or components, that are used to manufacture theproduct, and manually make associations of the parts with cost. Forexample, a process of manually establishing a projected cost of a partbased on physically identifiable features (e.g., the number of holes ina part) was used. That is, based on past experience it may have beendetermined that it took one minute to cut a hole in a part. Based on thecurrent labor rate, and the number of holes, the cost of the holes inthe part being reviewed could be estimated. Other features such as thiswere added together to project the cost of a part. This form of partreview may be performed for some parts. However, when the number ofparts is large, the process clearly becomes overwhelming. In addition,the reliability of manual review is suspect because it is dependent onreviewing physically identifiable features, and often misses underlyinginteractions that may impact cost.

The present invention is directed to overcoming one or more of theproblems set forth above.

SUMMARY OF THE INVENTION

In one aspect of the present invention, a computer based method ofanalyzing a plurality of parts, each of the parts having at least onepart characteristic is disclosed. The method includes the steps ofestablishing at least one repository of the part characteristics,establishing a relationship between at least a portion of the parts anda cost characteristic, and analyzing the portion of the parts inresponse to the relationship.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustration of one embodiment of a system associated withthe present disclosure;

FIG. 2 is an illustration of one embodiment of a method of analyzing aplurality of parts;

FIG. 3 is an illustration of one embodiment of a table of partsassociated with a repository;

FIG. 4 is an illustration of an exemplary relationship associated withall connecting rods in a repository with respect to the partcharacteristics weight, demand (or volume), and price (or cost); and

FIG. 5 is an illustration of box plots associated with the differentparts an exemplary supplier makes.

DETAILED DESCRIPTION

The present disclosure includes a system and method of analyzing aplurality of parts, each of the parts having at least one partcharacteristic. A part may be a product, an assembly, a component of anassembly or a standalone component. Non-limiting examples of parts mayinclude an engine and/or the parts associated with an engine, such as aconnecting rod, a transmission, a piston, a cylinder seal, flange, flywheel, hub, manifold, pulley, etc. However, as indicated, parts mayinclude anything that may be manufactured, assembled, or created. Partcharacteristics may include the part number, the type of material thepart is made of, the type of finish of the part, the production (volume)of a part, the production of a part during a time period, the sales of apart, the sales of a part during a time period, the cost of a part, thecost of part during a time period, the weight of a part, the number ofholes in a part, the supplier of a part, the type or category of a part,the profit associated with a part, the profit associated with a partover a time period, etc. Part characteristics may also include logisticand/or economic characteristics. Logistic characteristics may includethe transportation cost, transportation time, packaging cost, packagingtype, storage cost etc, associated with a part. Economic characteristicsmay include characteristics such as labor cost, material cost, materialsource etc. FIG. 1 illustrates one embodiment of a system 102 associatedwith the present disclosure. The system 102 may include a repository 104of part characteristics. The system 102 also includes a processor 106configured to establish a relationship between at least a portion of theparts (or part characteristics) and a pre-selected part characteristic(e.g., a cost characteristic), and then analyze the portion in responseto the relationship. The processor 106 may include one or morealgorithms configured to establish the relationship, or portionsthereof. In one embodiment, the system 102 may include multiple partcharacteristic repositories 104 a, 104 b, 104 c, etc. In addition, thesystem may be able to electronically communicate with other partcharacteristic repositories 108 a, 108 b, etc. The system 102 may alsoinclude a user interface 120. The user interface may include a display122. Alternatively the display 122 may be considered a separate device.

FIG. 2 illustrates one embodiment of a method associated with thepresent disclosure. In a first control block 202, at least onerepository of part characteristics is established. Establishing arepository of part characteristics may include identifying one or moreexisting repositories having part characteristics, creating a repositoryof part characteristics, or both. The part characteristic repository mayhave been established ahead of time, may be dynamically established, ora combination thereof. For example, the processor 106 may bepreprogrammed with the name or location of one or more existing partcharacteristic repositories. The identified repositories may include thepart characteristics, and/or addresses or electronic links to thelocation of the part characteristics or repositories that include thepart characteristics. In this manner, when the method associated withthe present disclosure is executed, the processor 106 knows whatrepository to access to acquire part characteristic information.Alternatively, the repository may be established (e.g., identified) inresponse to a user who may enter the name of a repository having thedesired part characteristic information. In one embodiment, theprocessor 106 is programmed with the identity or location of a partcharacteristic repository, and this repository may be overridden, orsupplemented by a user designated repository. In another embodiment,establishing a repository of part characteristics may include creating arepository of part characteristics. For example, in one embodiment, therepository may be established by creating a repository that includeselectronic links to the appropriate repositories that include theinformation. Therefore, the established repository may include one ormore links to other existing part characteristic repositories. The linksmay be activated when the part characteristic information is desired.Alternatively the established repository may be created by accessing theappropriate repositories having the part characteristic information, andelectronically transferring the information into the repository beingestablished, e.g., identified or created. Therefore the repository beingestablished may include the part characteristics, or links torepositories having the part characteristics.

In one embodiment, the part repository 104 may be established byestablishing the parts that are to be analyzed. The determination ofwhich parts are to be reviewed may be made by a user and entered througha user interface 120 (e.g., a part or part characteristic request),programmed into the processor 106, and/or contained in a repository ofparts which may be associated with the part repository 104, or aseparate repository. A part characteristic request may include one ormore of a part, part characteristic, particular value of a partcharacteristic (e.g., name of a particular supplier), etc. In oneembodiment, the processor 106 may automatically determine which parts toreview. For example, if a user enters a part type (e.g., bolt), theprocessor 106 may establish, or identify, all the parts that are bolts.Once the parts to be reviewed are identified, the repository 104 may beestablished. In one embodiment, the processor 106 may identify whichrepositories have the identified parts. In one embodiment, there is onlyone repository having all the part characteristics. Alternatively theremay be multiple part characteristic repositories. In this embodiment,the processor may use a pre-existing table that correlates a particularpart with one or more repositories having associated partcharacteristics. Alternatively, the processor 106 may access one or morerepositories to determine which repositories have associated partcharacteristic information.

In one embodiment, a repository 104 may include all, or a portion, ofthe part characteristics associated with a part. In one embodiment, thedesired part characteristics may be identified by a user and enteredinto the system via the user interface 120, or programmed into theprocessor 106 or contained in a repository 104, 108. Alternatively theprocessor may dynamically determine what part characteristics areassociated with a part, or what part characteristic information isavailable. For example, the processor 106 may access one or morerepositories to identify what part characteristics are available for aparticular part. Different repositories may contain different partcharacteristics, and different parts may have different characteristicsassociated with them.

Examples of repositories which may be accessed include one or morerepositories associated with: a repository of suppliers and the partsthat they provide, the cost of the parts, and the volume sold of theparts, a logistics repository that may include the part number, cost,volume, and supplier of the parts, and/or an engineering repositoriesthat may include the weight, surface finish, material etc.; of theparts. The engineering repositories may include or be associated withrepositories that have electronic drawings or images of the part. Thepart characteristics may be included in one or more of the repositories.For example, the weight of a part may be included in the logisticsrepository and the engineering repository. In one embodiment, one ormore part characteristics may be manually entered by the user.

In one embodiment, the repository may be established based on a partcharacteristic to be analyzed. For example, the user may enter a partcharacteristic to be analyzed, irrespective of the type of partassociated with the part characteristic. The processor 106 may thenestablish a repository of parts having the designated partcharacteristic. For example, the processor 106 may access one or morerepositories to identify the parts having the desired partcharacteristics. The repository may be established based on informationassociated with one or more parts, or one or more part characteristicsassociated with the parts.

In one embodiment, establishing a repository of part characteristicsincludes formatting the part characteristic information appropriately,and verifying the information being established. For example, ifmultiple repositories contain a weight of a part, the system 102 maycompare the two weights to see if they match. The weight listed in anengineering specification repository may be different from the weightlisted in a logistics repository. The discrepancy may be caused by thelogistics repository taking into account the shipping weight that mayinclude a shipping container associated with the part. Therefore, theremay be discrepancies in the information obtained by the system 102.Discrepancies may be resolved in several ways. For example, the user mayhave established a repository hierarchy or priority such that when adiscrepancy occurs, part characteristics from one repository may begiven deference, or priority, over the value of the same partcharacteristic received from a different repository. The repositoryhierarchy may be dynamically identified by a user, or pre-programmedinto the process 106. In one embodiment, the user may specify what partcharacteristics should be retrieved from which repositories. Therefore,there are no discrepancies since the system takes the value identifiedfor the part characteristic from the designated repository, and ignoresother values available in other repositories. In another embodiment, thesystem may notify the user when a discrepancy is identified, and let theuser resolve the discrepancy. Other forms of discrepancies may includefinding no value associated with a particular part characteristic, orfinding a value that is out or range. For example, a repository of partprices has a part listed, but may have no associated price. In addition,a part may be listed that has a price that is out of bounds, e.g., abolt with a piece part price of $1,000,000. These discrepancies may beidentified by bounds, or range checking. The user may be notified ofthese discrepancies.

In a second control block 204, a relationship between at least a portionof the parts, and a part characteristic is established. The partcharacteristic may be a pre-selected part characteristic such as a partcharacteristic that has be programmed into the system 102, or that isdynamically determined based on a user input, or a combination thereof.The parts selected to establish the relationship may include all parts,or parts associated with particular part characteristic, e.g., ofsimilar part type, or from the same supplier etc. For example, therepository may include parts associated with part types such asconnecting rods, flywheels, manifolds, pulleys etc. The parts that areconnecting rods may be selected (i.e., the part type connecting rod maybe selected). A relationship between the part characteristics ofselected parts and a pre-selected part characteristic (e.g., cost) maybe established. For example, analysis techniques may be used toestablish the cost of a part as a function of one or morecharacteristics of the parts, such as the weight, material type, volumeof a part, supplier, finish, etc. The information (or values) associatedwith the part characteristics may be used to establish the relationshipbetween the parts and/or characteristics and the pre-selectedcharacteristic.

The type of analysis used to establish the relationship isimplementation dependant and may vary as a function of the data providedto the algorithm establishing the relationship, and/or the informationbeing requested (e.g., part analysis request). The analysis may bedependent on the number of dependent variables and/or independentvariables that are being analyzed in the relationship and/or theobjective of the analysis being performed. For example, the analysis mayinclude the use of classical, Bayesian, and/or machine learningtechniques. Classical analysis techniques may include multivariatestatistical techniques simple regression, multiple regression, factoranalysis, item analysis multivariate analysis of variance, discriminateanalysis, path analysis, cluster analysis, multidimensional scaling,and/or least squares estimation. In one embodiment, multiple regressionmay be used to determine the relationship between one dependent variable(e.g., a part characteristic such as cost) and multiple independentvariables (i.e., multiple other part characteristics, such as weight,type of material, etc.). Other techniques, such as in factor analysis,cluster analysis, and multivariate techniques may be used when thedesired relationship is associated with multiple dependent variables andmultiple independent variables. Generic model-fitting or classificationalgorithms e.g., neural networks (e.g., back propagation, feed-forwardnetworks etc.), meta-learning techniques such as boost etc., may beapplied for predictive data mining. Predictive data mining techniquesmay be desired when the accuracy of a prediction is of higher priority,regardless of whether or not the models or techniques used to generatethe prediction is interpretable or open to simple explanation. That is,data mining techniques may be desired when the objective is to predictthe price of a future part, as opposed to analyze the existingrelationship among the parts. As mentioned, the selection of theparticular analysis technique(s) is implementation dependent and may bebased on factors such as user preference, the data to analyze, and thenumber of dependent and/or independent variables, the objectives of theanalysis. Therefore, as will be discussed below, the user may specifythe analysis techniques to be used, or the system 100 may determine theappropriate technique(s) to use.

Additional analysis configuration may be performed on a selected orpotential analysis technique. By way of example only, if multipleregression is the analysis technique used, an equation associated withthe relationship may be: Y=b1X1+b2X2+ . . . bnXn+c, where the b's arethe regression coefficients, representing the amount the dependentvariable Y (e.g., the part characteristic cost) changes when theindependent variable (the X's, e.g., the other part characteristics)change 1 unit. The c is the constant, where the regression lineintercepts the y axis, representing the amount the dependent Y will bewhen all the independent variables are O. In one embodiment, adetermination may be made regarding whether any transformation (e.g.,log functions, square roots, etc.) are needed to the proposedrelationship (or equation). For example, should the log of a partcharacteristic be used in the relationship, should the square root of apart characteristic be used in the relationship etc. As will bediscussed, the form of the equation, e.g., whether one or moretransformations are used, may be determined by the user, by the system102, or a combination thereof.

In one embodiment, different relationships may be created, e.g., usingdifferent transformations or different part characteristics for themultiple regression analysis, and analyzed to determine whichrelationships perform better than others. Goodness of Fit analysistechniques such as R2, RMS, P Value, F ratios, standard error etc., maybe used to establish performance characteristics of the relationships.For example, techniques such as R2, which establish the percent ofvariance in the dependent variable (e.g., the part characteristic cost),explained collectively by the independent variables (e.g. the other partcharacteristics). By using R2, for example, an assessment may be maderegarding which relationship best explains the variance in the dependentvariable in response to the independent variables. RMS provides anindication of which model best predicts future aspects of a part, orpart to be designed.

Therefore, in one embodiment, a threshold level of performance may beestablished for the relationship. If the relationship does not meet thethreshold level of performance, then the user may be notified that theestablished relationship does not meet the desired level of accuracy,the desired level of ability to explain the variance in the dependentvariable in response to the independent variables, or desired level ofability to predict future characteristics of the part. If multiplerelationships are being compared with each other, and none of themexceed the desired level of success, then the user may be notified ofwhich relationship performed best, but that none of them met the desiredthreshold. If multiple relationships are tested and one or more exceedthe threshold, the best one may be selected, or they may all be providedto the user for selection.

In one embodiment, the system 102 may also establish which partcharacteristics are more relevant to the relationship than others. Inthis embodiment, part characteristics that are not significant to therelationship may be removed from the analysis, or analysis portion ofthe system 102. In one embodiment the relevance of the partcharacteristics may be established by analyzing the establishedrelationship. For example, consider the simplistic equation:

Part Cost=10+8*(part weight (Kg))−4*(part demand). In this example, anincrease in weight by a Kg will increase the cost by 8, while andecrease in demand by 1 will increase the cost by 4. There isapproximately a 2:1 ratio between weight and demand, indicating thatweight has more of an influence on price than demand does. Therefore, acomparison of coefficients may be performed to establish the influence(or sensitivity), or relative influence of one part characteristicversus another. In one embodiment, the system 102 may utilize additionalstatistical analysis to establish the relevance of the independentvariables and/or to select which variables to use in the relationship.Applicable techniques such as stepwise multiple regression (includingforward selection, or backward elimination), forced entry, forcedremoval, and hierarchical multiple regression may be used. For example,multiple regression analysis may be used to establish a relationshipbetween all of the independent variables (e.g., part characteristics),and the dependent variable (the part characteristic cost). Therelationship establishes a relative influence of the independentvariables. Then, forward selection (associated with stepwise regression)may be used to determine the relevance of the variables. Forwardselection may begin with no independent variables in the equation(associated with multiple regression). The independent variable havingthe highest correlation, or influence, with the dependent variable maybe added into the equation. The performance of the resulting equationmay be determined using the assessment techniques previously discussed,such as R2. The process may be repeated, adding another independentvariable (and associated coefficient) to the equation, and thenassessing the equation. Once all the independent variables have beenadded, the assessment metrics (e.g., R2) may be compared to determinewhich equation best described the relationship. The variables in theequation that best describes the relationship may be considered to bethe most relevant variables, and the other variables may be ignored. Forexample, a determination may be made regarding which variable (orcharacteristic) configuration resulted in the highest R2, or noticeableimprovements in R2. Alternatively, each time an independent variable isadded, the relationship is assessed to see if there was a noticeableimprovement (e.g., was R2 increased by an appreciable amount). If theassessment metric was not increased by a significant amount, then theprocess may be stopped, and the independent variables currently formingthe relationship may be deemed to be the most relevant. The amount ofincrease in R2 that triggers the completion of the process isimplementation dependent.

The backward elimination process (associated with stepwise regression)begins with all the independent variables in the equation andsequentially removes them, analogous to the forward process, todetermine the desired relationship. For example, after establishing therelative influence of the independent variables, the least influentialindependent variable may be removed from the equation. If the resultingR2 is not significantly reduced, then the process may be repeated. Inone embodiment, stepwise regression may be used when constructing theequation, or to prune the variables (or characteristics) used inestablishing the equation.

In one embodiment, the system 102 is configured to automatically form arelationship between the selected part characteristics and thepre-selected characteristics (e.g., cost). The system may automaticallydevelop multiple relationships, using a different analysis technique,and/or different transformations for the technique, and/or differentindependent variables in the relationships. The results may then becompared to determine which relationship most accurately describes therelationship. For example, techniques such as R2 may be used toestablish the accuracy of each relationship (or model). The resultingcomparison may be used to select the most accurate relationship. In oneembodiment, the system 102 may step establish relationships based on allof the available techniques (e.g., a toolbox of Classical, Bayesian, andMachine learning techniques, and/or a combination thereof), and thencompare the performance capabilities to establish the most appropriaterelationship(s). Alternatively the system 102 may select analysistechniques based on analysis characteristics, such as the number ofdependent variables to be analyzed, the number of independent variablesto be analyzed, the objective of the analysis, the type of datainvolved, and/or the class of problem at issue. As will be described, inone embodiment, the user may enter one or more of the above analysischaracteristics. In one embodiment, multiple relationships may beestablished to support different analysis objectives, e.g., to analyze arelationship among current parts or predict the characteristic of afuture part. Therefore, the user may enter the analysis technique(s) touse, the system 102 may recommend analysis technique(s) to use based onuser inputs, or the system 102 may automatically establish thetechniques to be used so the user doesn't have to select a desiredtechnique and/or associated technique configuration information.

In one embodiment, at least one economic characteristic may be includedwhen establishing the relationship. Economic characteristics may includelabor cost characteristics, inflation characteristics, a nationaleconomic index characteristics, and an industry economic indexcharacteristic. In one embodiment, the economic and logisticcharacteristics may be used to normalize or offset external influenceson the part characteristics. The economic and logistic characteristicsmay also be used to establish which parts are more susceptible toexternal influences or characteristics and to establish which externalcharacteristics most influence the part characteristics. The partcharacteristics, logistic characteristics and economic characteristicsmay be associated with time periods. Therefore, the relationship mayrepresent the relationship among the part characteristics, logisticcharacteristics, economic characteristics, and the pre-selected partcharacteristic, e.g., cost.

In one embodiment the system 102 may also establish confidence factorsassociated with the relationship, or results of the relation ship. Theconfidence factor may be based upon a single result (e.g., 70% sure thatthe result is $10/part, or upon a range of results (95% sure that theresult is between $9 and $11/part).

In a third control block 206, at least a portion of the parts areanalyzed in response to the relationship. The analysis is implementationdependent. The present disclosure provides for versatile analysis suchthat the user may configure the analysis for any aspect of the part orassociated part characteristics. The analysis may include identifyinganomalies in the relationship. For example, assume the part categoryanalyzed is connecting rods, that there are twenty different types ofconnecting rods, and that there are four different suppliers of theconnecting rods. The established relationship may be analyzed withrespect to the different suppliers. For example, does any one supplierstand out as being more expensive than the others? Do suppliers havedifferent specialties, e.g., have lower cost than the others whendealing with a particular material type? Does one supplier have betterrates than others when volumes are low? How does a current suppliercompare with a previous supplier, or a proposed future supplier? Theestablished relationship may be analyzed with respect to one or morepart characteristics, e.g., cost drivers. For example, what are thepredominant cost drivers of the part, e.g., weight, material type,finish type, volume etc.? What would a future connecting rod cost basedon this relationship. An engineer, for example, may have a theoreticalor simulated design for a connecting rod. However, before prototypes ofconnecting rods are built, the established relationship may be used todetermine what the projected cost of this connecting rod will be, e.g.,based on projected weight, material type, volumes sold, supplier used,etc. In one embodiment, a confidence factor may be associated with thepredicted values. For example, the confidence factor may be based on thesquared standard error of mean predicted scores, the mean squareresidual, both of which may be obtained from typical regression outputs.In addition confidence factors associated with a value and/or a range ofvalues may be established with machine learning techniques. If thepredicted cost is too high, the engineers may consider differentmeasures to reduce the cost in response to the cost drivers identifiedby the relationship, use a different design, use an existing part, use adifferent material, use a different supplier etc. In addition, if newmaterial types are being considered, relationships associated with otherparts of the material type may be analyzed to determine the costeffectiveness of the material type, and help make cost projections forthe proposed part. Warranty and reliability predictions may also be madebased on the part characteristics, and established relationship.

In one embodiment, if the economic characteristics and/or logisticcharacteristics are used in establishing the relationship, then analysismay be performed to determine the impact of economic and/or logisticfactors on the relationship. For example, if a supplier providesmultiple parts, but one of the parts seems overly expensive relative tothe other parts and other suppliers, were there any economiccharacteristics that impacted the supplier that might not have impactedthe others. For example, the parts were supplied during a particularinterval in which labor cost were excessive, or there was a strike andan alternative work force was being used. In addition, there may belogistic factors impacting the cost (e.g., transportation or packagingcost). Therefore, these economic characteristics may have impacted thisparticular supplier during a discrete time period, and in such a waythat other suppliers were not effected. This information may be used toavoid over-reacting to a problem that was temporary, and to interactwith the impacted supplier to determine why the cost were higher andwhat can be done in the future to reduce the cost.

Industrial Applicability

The present invention includes a method and system configured to analyzea plurality of parts. Each of the parts has at least one partcharacteristic. The method includes the steps of establishing at leastone repository of part characteristics, establishing a relationshipbetween at least a portion of the parts and a part characteristic, andanalyzing the portion of the parts in response to the relationship.

In one embodiment, a repository of the characteristics associated withparts may be established. The type or number of parts to be included inthe repository is implementation dependent. In one embodiment, therepository may include part characteristics for all of the partsassociated with a company, e.g., the company who owns the parts.Alternatively, the part characteristics may be associated with a portionof the company, such as a particular department or group. The repositorymay exist, or may be dynamically created, or a combination thereof. Thepart characteristics may be for a particular part type or supplier. FIG.3 illustrates one embodiment of a table of parts associated with therepository. The table may illustrate the part numbers (rows) as afunction of the part characteristics (columns). The data associated withthe table may be physically stored in the repository 104. Alternatively,some or all of the data may be established by dynamically accessingother repositories. For example, based on links stored in the repositorythat enable an electronic connection to be made to another repository toaccess the information. For example, information associated withengineering specifications may be stored in a separate repository, andaccessed when needed.

In one embodiment, the user may interact with a user interface 120 toselect the parts (or part characteristics) the user would like toanalyze (e.g., part characteristic request). The user interface 120 mayenable the user to select (e.g., via a pull down menu or data entryprompt) among part types to analyze, e.g., flywheel, pulley, sleeve,connecting rod, flange, and/or adaptor, other, or All Parts. “Other” maybe used to enter a request for information associated with a part, orpart characteristic the system 102 hasn't dealt with, e.g.,characteristics associated with a new part in a repository that haven'tbeen accessed by the system 102. In addition the user interface mayenable the user to select among suppliers to analyze, e.g., supplier A,supplier B, and/or supplier C, or All Suppliers. That is, the partsprovided by one or more specific suppliers may be analyzed. The userinterface (e.g. through pull down menus, data entry capability etc.) mayenable the user to select among part characteristics to analyze, e.g.,part type, material type, finish type, weight, volume etc. For example,the user may select a part and be presented with the available partcharacteristics associated with the part, with which to configure theanalysis. In one embodiment, a user may enter a part characteristic, andbe presented with all the available parts (or part types) having thatpart characteristic. In one embodiment, the user may select a timeperiod associated with the analysis, e.g., all part data from the last 5years, or all part data associated with a particular part characteristicfrom the last 5 years, etc. In one embodiment, time based data may benormalized (e.g., to account for inflation etc.), such that theunderlying causes of cost may be further analyzed. In this manner, theuser may configure the parts analysis relative to their specificdesires. The selection of the parts to be analyzed may be as broad ornarrow as the user desires, and the associated analysis may be as broador narrow as they desire.

Once the parts to be analyzed have been established, the system 102develops a relationship between the characteristics of the selectedparts and a part characteristic of the parts (e.g., cost). In oneembodiment, the user may select the analysis technique to use, thetechnique configuration to use, and/or the performancetechnique/criteria to use. In an alternative embodiment, the user mayenter some analysis characteristics e.g., objectives of the analysis, ornumber of dependent variables and the number of independent variablesetc. The system 102 may recommend certain analysis techniques, techniqueconfigurations, and/or performance techniques/criteria to the user basedon the analysis characteristics established by the user. The user maythen select the desired techniques etc., to establish therelationship(s). In one embodiment, the system may automaticallyidentify an appropriate analysis technique(s) and/or. configuration,and/or performance criteria, with or without user established analysischaracteristics. For example, the system 102 may provide a list ofanalysis techniques from which to select. One of the selections may beAutomatic, or Best Fit, meaning the user would like the system 102 todetermine and apply the most appropriate analysis technique. In thelater case, the system will develop a relationship among the partcharacteristics and pre-selected part characteristic (e.g., cost) usingapplicable analysis techniques. The system 102 may then apply anassessment criteria (or accuracy technique), e.g., R², to determinewhich relationship was the most accurate or most appropriate. Asmentioned, some of the analysis characteristics the system 102 mayaccount for in determining the appropriate relationships are: how manydependent variables and independent variables are being analyzed, whatis the objective of the analysis, e.g., is the relationship to be usedfor future part cost projections, current relationship analysis, orboth. The user may be prompted for these characteristics through theuser interface and/or display. For example, the user may be prompted toenter the dependent variable(s) (e.g., cost characteristic). The usermay select from a menu having all part characteristics, or may beprompted to enter the data. In addition, the user may be prompted forthe independent variables. The may be provided a list of all availablepart characteristics, and the option “All”. The option “All” would thenselect all of the part characteristics (except the dependent variables)for the independent variables. The system 102 may use these analysischaracteristics to select an analysis technique. If the establishedrelationship does not meet an established threshold, the system 102 mayidentify another technique to develop the relationship. Alternatively,the system 102 may develop multiple relationships using all applicabletechniques and then compare the established relationships to determinewhich, if any, are most appropriate. For example, if the user selectscost as the dependent variable, and “All”, as the independent variable,and selects as the objective: Existing Parts Analysis (as opposed toCharacteristic Predictions) then the system 102 may select multipleregression as the analysis technique (e.g., select classical techniquesbased on the analysis characteristics, and then further selecttechniques such as multiple regression based on the number of dependentvariables and the number of independent variables). If severaltechniques may be applicable to the analysis characteristics, then thesystem 102 may test the techniques, or further develop theconfigurations of the techniques before testing. In one embodiment, thesystem 102 may select multiple regression, and then develop multiplerelationships to determine what, if any, transformations are needed, andwhat the relevant part characteristics are. FIG. 4 illustrates anexemplary relationship associated with all connecting rods in therepository with respect to the part characteristics weight, demand (orvolume), and price (or cost). The relationship was established usingmultiple regression analysis

Upon completion of the relationship, the parts may be analyzed inresponse to the established relationship. In one embodiment, the systemmay provide the user with several techniques to view the establishedrelationship and associated analysis. The display techniques, orformats, may include representing the relationship and/or analysis as asurface plot, histogram, box plot or other technique for graphicallyrepresenting information. The user may provide a display requestindicative of the desired manner to view the relationship or associatedanalysis. For example, FIG. 4 illustrates the relationship of costversus weight and demand of connecting rods, in the form of a surfaceplot. With reference to FIG. 4, if the user would like to predict theprice of a connecting rod being currently designed, they may enter apredicted weight of the connecting rod, and predicted sales volume ofthe connecting rod, and the system will determine the predicted price ofthe connecting rod based on the established relationship. The system 102may provide a confidence factor associated with the prediction. Whilethe analysis technique associated with FIG. 4 was multiple regressionanalysis, other relationships using different types of analysis such asmachine learning may have been established. For example, multiplerelationships may be developed such that if the user desires todetermine future characteristics, they may use the appropriate model, orif they desire to analysis current part characteristics they have theappropriate model available. That is the relationships have beenestablished for seamless user analysis. Alternatively, if the userattempts to analyze the data in a manner in which the relationship isnot the most appropriate, the system 102 may run additional analysis toestablish the most appropriate relationship for the user's requestedanalysis.

In one embodiment, the user may highlight a particular point in therelationship, e.g., an outlier 402, and obtain information about thepoint, as illustrated in FIG. 4. An outlier is a data point that liesoutside the general map defined by the established relationship. Whenthe point is highlighted, an additional information box 404 may appear.The information box 404 may indicate the characteristics of the partassociated with the point, e.g., part number, supplier, weight, demand,price; use, etc. The information box 404 may indicate the actual partcharacteristic information 406 of the point 402, and also the expectedpart characteristic information 408 of the point 402, based on therelationship. That is, expected part information may be based on theprojected part information based on the relationship established (e.g.,the surface map). This may be done graphically, or textually. In thismanner the information box 404 is providing target (or expected values)to obtain. In one embodiment, the expected and actual values may bedisplayed in order of how far from the expected values the actual valueswere. Alternatively, the values will be displayed in order ofimportance. For example if the actual weight is off by 2 Kg, and volumeoff by 3 units, and the relative influence is 2:1 (an increase in one Kghas twice the impact on cost that a decrease in 1 unit sold has), thenweight may be shown first because it contributed the most to thedifference between actual and expected price. In one embodiment theinformation displayed in the information box may be normalized, e.g.,relative to how much difference there is between the actual and theexpected values. In one embodiment, the point to be analyzed, e.g., anoutlier, may be activated, e.g., clicked on, in which case aninformation screen is displayed. The information screen may provide thesame information as the information box 404 described above. Theinformation screen may provide additional information about the outlier402, and provide recommendations on what actions to take in order toenable the outlier to conform to the established relationship. Forexample, in one embodiment, the system may compare analogous partcharacteristics to establish the difference between the outlier andanalogous data points. For example, surrounding points may not besurface finished, which reduces their cost. Therefore, therecommendation may be to avoid surface finishing if possible. The system102 may establish that the outlier is a part manufactured by Supplier A.The system 102 may compare all of the connecting rods (for example) madeby Supplier A and establish that generally, Supplier A's parts aredefined by the established relationship, and that predominatelySupplier's A's parts are high volume parts. However, the outlier is alow volume part. Therefore, the system may notify the user, e.g.,through the information box 404, or information display, that the priceof this specific part is an outlier 402 in the general relationship ofthe connecting rods, that the part is an outlier relative to the otherparts supplied by Supplier A, and that the other parts supplied bySupplier A are high volume parts. Therefore, Supplier A may havedifficulty cost effectively supplying low volume parts. Therefore, ifSupplier A is unwilling, or unable to reduce their price, then asupplier that is more cost effective for low volume parts may beidentified and engaged. In one embodiment, the user is presented optionson how to view or analyze the data. For example, the user may selectconnecting rods for analysis. The user may identify an outlier, e.g., asillustrated in FIG. 4. The user may then enter the name of the supplierin a data entry portion, or the user may activate the supplier name inthe information box 404 (e.g., click on “Supplier A” displayed in thetext box. The system_102, may then establish the relationship (orestablish the displays based on the existing relationships) such thatthe parts associated with “Supplier A” may be displayed. Therelationship associated with parts supplied by “Supplier A” may then beanalyzed further. In this manner, the user is able to seamlessly movethrough the desired parts analysis. In another example, if the otherparts in the general area of the expected value of the outlier arebrackets made of aluminum, and the outlier is made of steel, the systemmay recommend using one of the other brackets, or changing the materialof the outlier to aluminum. In one embodiment, the information displaymay also provide a link to an electronic drawing of the part, and anysystem identified comparable parts. In this manner, the user mayactivate the link and view the electronic drawings of the part. This mayenable the user to quickly view the outlier to assess if there isanything visually unique about the part, and also to make an initialcomparison of the outlier part with analogous parts to determine ifanother part may be used instead. While outliers have been used todiscuss the functionality of the system 102, any of the data pointsviewed, or relationship maps/plots may be highlighted or selected inorder to obtain additional information/analysis. In one embodiment, thesystem may compare the part characteristics of the outlier with otherparts in the general area of the expected value, and identify anydifferences. That is, the system may recommend a more cost effectivepart, that already exists.

In one embodiment, the user may establish a relationship associated witha particular supplier, all of the parts they provide, and associatedcost. Then the relationship may be analyzed, for example, to determinethe average cost of the different part types, as illustrated in FIG. 5.FIG. 5 illustrates box plots associated with the different parts aparticular supplier makes. The box plot illustrates a distribution ofthe part cost for the associated parts. For example, the box plotillustrates the average part cost 502 (or alternatively the mean), the20% distribution 504, the 70% distribution 506, and associated outliers508. The resulting analysis may indicate which parts the supplier iscost effective on, and which ones they are not, and which parts thesupplier is cost effective on relative to their own capability. Theanalysis may be used as a focal point for discussions with the supplierto determine why they are more expensive in providing pulley's thantheir other parts. In addition, analysis may be performed to determinewhy some distribution ranges are larger than others. For example, whythe distribution range on pulleys is more than flywheels. In oneembodiment, one of the data points, e.g., an outlier 506, may behighlighted, and the characteristics of the part may be illustrated,e.g., with an information box, or information display. In addition, thedata point (or part) may be highlighted, and the user may be providedthe option of displaying the established relationship map between costand the other part characteristics, an example of which is illustratedin FIG. 4. If the relationship map (or surface) does not already exist,the system may build it when requested. In this manner the informationmay be manipulated from one representation to another based upon theestablished relationship, thereby providing user requested informationthat describe and explain the relationships among the parts. In oneembodiment, box plots of multiple suppliers may be displayed next toeach other, i.e., corresponding parts located next to each other, suchthat the user may understand how suppliers compare in general ondifferent part types. In one embodiment, the user may highlight aparticular part, e.g., an outlier on a surface plot, and then select(e.g., through a pull down menu, or pop up menu activated byhighlighting the part and activating a mouse) the desired manner ofviewing the associated relationship/displays, such as a box plotassociated with the supplier of the part, a box plot associated with allsuppliers, a plot of parts having the same material, a normalization ofthe part or one or more characteristics of the part. In another example,a normalized relationship, discussed below, may illustrate that anoutlier part, which was heat treated, is actually in line with otherheat treated parts from the same supplier, or other suppliers.Therefore, the reason this selected part was an outlier may beestablished to be due to the fact that it was heat treated and the otherparts from the same supplier, e.g., other pulley parts were not.

In one embodiment the relationship associated with the partcharacteristics may be normalized. For example, the connecting rodslocated on the surface of the map illustrated in FIG. 4 may be made ofaluminum, and the outlier 402 made of steel. There may be a 2:1 costdifference between steel and aluminum. Therefore, if normalized the datapoint of the steel part may move down to the surface, or close to it. Bynormalizing one or more characteristics, the readily explainable factorsassociated with why a part is an outlier may be accounted for, leavingthe outliers to mainly represent unexplained deviations. Therefore, inone embodiment, the user may select an option to normalize the partcharacteristics associated with a surface. Alternatively they maynormalize the part characteristics associated with a particular part Inanother embodiment, the user may normalize a particular characteristicof a part to determine the impact (or reduce the impact) of that oneparticular characteristic, thereby visually identifying other featuresthat may be causing the data point to be an outlier. For example, thematerial cost (or material type) may be normalized to determine theimpact on the relationship. In one embodiment, the user may enter thenormalization factors (e.g., steel is twice the cost of aluminum).Alternatively, the normalization factors may be stored in the system102, or dynamically determined based on factors such as current laborrates, transportation rates, material cost etc.

In one embodiment, there may be multiple surfaces plotted based on thepart characteristics. For example, there may be a surface associatedwith heat treated connecting rods, and a surface associated with nonheat treated rods. In this scenario, the two maps may be normalized, oradjusted to account for the impact of the particular characteristic(e.g., expense of the heat treatment process). When multiple surfacesare mapped in the same graph, the intersection of the two surfaces, ifthere is one, provides insight into the crossover point from where it ismore cost effective to use aluminum (for example) to where it is morecost effective to use steel. This data helps establish when to use onepart characteristic over another (e.g., material, material finish etc.)

Other aspects, objects, and advantages of the present invention can beobtained from a study of the drawings, the disclosure, and the claims.

What is claimed is:
 1. A computer based method of analyzing a pluralityof parts, each of the parts having at least one part characteristic,comprising; establishing at least one dynamically accessible repositoryof said part characteristics using a computer processor; establishing arelationship between at least a portion of said parts and at least oneof said part characteristics using said computer processor; andanalyzing said portion of said parts in response to said relationshipusing said computer processor, wherein the step of establishing saidrelationship further comprises: establishing a part category;associating at least a portion of said parts with said part categorybased upon at least one of said characteristics of said part; andestablishing said relationship between said associated parts and a costcharacteristic.
 2. A method, as set forth in claim 1 , wherein the stepof establishing said at least one part characteristic repository furthercomprises the step of receiving at least a portion of said partcharacteristics from a second repository.
 3. A method, as set forth inclaim 2, wherein said second repository is a repository of drawings. 4.A method, as set forth in claim 1, wherein said part characteristicsincludes at least one of a cost, a weight, a material type, a finishtype, and a volume.
 5. A method, as set forth in claim 1, wherein saidpart characteristics includes a volume characteristic associated with atleast one time period.
 6. A method, as set forth in claim 1, whereinsaid part characteristics are associated with at least one time periodand further comprising: establishing at least one economiccharacteristic associated with said time period.
 7. A method, as setforth in claim 1, wherein the step of establishing said relationshipfurther comprises the step of: automatically establishing an analysistechnique; and establishing said relationship in response to saidanalysis technique.
 8. A method, as set forth in claim 7, wherein thestep of automatically establishing said analysis technique furtherincludes the step of automatically establishing said analysis inresponse to said part characteristics associated with said portion ofsaid parts.
 9. A method, as set forth in claim 7, wherein the step ofautomatically establishing said analysis technique further includes thestep of automatically establishing said analysis technique in responseto a parts analysis objective.
 10. A method, as set forth in claim 9,wherein said parts analysis objective is one of a characteristicprediction and a relationship explanation.
 11. A method, as set forth inclaim 7, wherein said relationship includes a number of dependentvariables, and further wherein the step of automatically establishing ananalysis technique further comprises the step of: automaticallyestablishing said analysis technique to establish said relationship inresponse to said number of dependent variables.
 12. A method, as setforth in claim 7, wherein said analysis technique is one of a classicaltechnique, a Bayesian technique, and a machine learning technique.
 13. Amethod, as set forth in claim 12, wherein the step of automaticallyestablishing said analysis technique further includes the step ofautomatically establishing said analysis technique in response to aparts analysis objective.
 14. A method, as set forth in claim 13,wherein said parts analysis objective is one of a characteristicprediction and a relationship explanation.
 15. A method, as set forth inclaim 14, wherein said classical technique is established in response tosaid objective being said relationship explanation.
 16. A method, as setforth in claim 15, wherein said machine learning technique isestablished in response to said objective being said characteristicprediction.
 17. A method, as set forth in claim 16, wherein said portionof said parts include a plurality of relevant characteristics, furthercomprising the step of automatically establishing said relevantcharacteristics.
 18. A method, as set forth in claim 1, wherein the stepof establishing said relationship further comprises the step ofautomatically establishing a plurality of relationships using aplurality of analysis techniques.
 19. A method, as set forth in claim18, wherein the step of establishing said relationship further comprisesthe steps of: establishing an accuracy of said relationships;establishing said relationship in response to said relationshipaccuracy.
 20. A method, as set forth in claim 19, wherein the step ofestablishing said relationship accuracy further comprises the step ofautomatically establishing an accuracy technique to establish saidrelationship accuracy.
 21. A method, as set forth in claim 20, whereinthe step of automatically establishing said accuracy technique furtherincludes the step of automatically establishing said accuracy techniquein response to a parts analysis objective.
 22. A method, as set forth inclaim 21, wherein said parts analysis objective is one of acharacteristic prediction and a relationship explanation.
 23. A method,as set forth in claim 22, wherein said portion of said parts include aplurality of relevant characteristics, further comprising the step ofautomatically establishing said relevant characteristics.
 24. A method,as set forth in claim 1, wherein the step of analyzing said portion ofsaid parts in response to said relationship further comprises the stepof establishing at least one cost driver in response to saidrelationship.
 25. A method, as set forth in claim 1, wherein the step ofanalyzing said portion of said parts in response to said relationshipfurther comprises the step of establishing an anomaly in response tosaid relationship.
 26. A method, as set forth in claim 1, wherein thestep of analyzing said portion of said parts in response to saidrelationship further comprises the step of establishing a normalizedcost driver in response to said relationship.
 27. A method, as set forthin claim 1, wherein the step of analyzing said portion of said parts inresponse to said relationship further comprises the step of comparing aplurality of suppliers in response to said relationship.
 28. A method,as set forth in claim 1, wherein the step of analyzing said portion ofsaid parts in response to said relationship further comprises the stepof comparing a plurality of parts supplied by a supplier in response tosaid relationship.
 29. A method, as set forth in claim 1, wherein thestep of analyzing said portion of said parts in response to saidrelationship further comprises the step of establishing a supplierstrength in response to said relationship.
 30. A method, as set forth inclaim 1, wherein the step of analyzing said portion of said parts inresponse to said relationship further comprises the step of establishinga supplier weakness in response to said relationship.
 31. A method, asset forth in claim 1, wherein the step of establishing at least onerepository further comprises the steps of: establishing a partcharacteristic request; and retrieving one or more parts from anexternal repository in response to said part characteristic request. 32.A method, as set forth in claim 1, wherein the step of establishing saidat least one repository further comprises the steps of: establishing apart characteristic request; and retrieving one or more partcharacteristics from an external repository in response to said partcharacteristic request.
 33. A computer based method of analyzing aplurality of parts, each of the parts having at least one partcharacteristic, comprising; establishing at least one dynamicallyaccessible repository of said part characteristics using a computerprocessor; establishing a relationship between at least a portion ofsaid parts and at least one of said part characteristics using saidcomputer processor; and analyzing said portion of said parts in responseto said relationship using said computer processor, wherein the step ofestablishing said at least one part characteristic repository furthercomprises the step of receiving a first portion of said partcharacteristics from a first repository and a second portion of saidpart characteristics from a second repository.
 34. A computer basedmethod of analyzing a plurality of parts, each of the parts having atleast one part characteristic, comprising; establishing at least onedynamically accessible repository of said part characteristics using acomputer processor; establishing a relationship between at least aportion of said parts and at least one of said part characteristicsusing said computer processor; and analyzing said portion of said partsin response to said relationship using said computer processor, whereinsaid part characteristics are associated with at least one time periodand further comprising establishing at least one economic characteristicassociated with said time period and wherein said part characteristicassociated with said relationship is a cost characteristic, and whereinthe step of establishing said relationship includes the step ofestablishing said relationship between at least a portion of said partcharacteristics, said cost characteristic, and said economiccharacteristic.
 35. A computer based method of analyzing a plurality ofparts, each of the parts having at least one part characteristic,comprising; establishing at least one dynamically accessible repositoryof said part characteristics using a computer processor; establishing arelationship between at least a portion of said parts and at least oneof said part characteristics using said computer processor; andanalyzing said portion of said parts in response to said relationshipusing said computer processor, wherein said part characteristics areassociated with at least one time period and further comprisingestablishing at least one economic characteristic associated with saidtime period and wherein said at least one economic characteristicincludes at least one of a labor cost characteristic, an inflationcharacteristic, a national economic index characteristic, and anindustry economic index characteristic.
 36. A computer based method ofanalyzing a plurality of parts, each of the parts having at least onepart characteristic, comprising; establishing at least one dynamicallyaccessible repository of said part characteristics using a computerprocessor; establishing a relationship between at least a portion ofsaid parts and at least one of said part characteristics using saidcomputer processor; and analyzing said portion of said parts in responseto said relationship using said computer processor, wherein the step ofestablishing said relationship further comprises the steps of:establishing a plurality of relationships between at least a portion ofsaid parts and said cost characteristic; establishing an accuracycharacteristic for each of said plurality of relationships; andestablishing said relationship in response to said accuracycharacteristics.
 37. A method, as set forth in claim 36, furthercomprising the step of establishing at least one of said partcharacteristics of said portion of parts, as a cost driver, in responseto said established relationship.
 38. A method, as set forth in claim37, wherein the step of analyzing said portion of said parts comprises:establishing a future part, said future part having at least one partcharacteristic; establishing a cost characteristic associated with saidfuture part in response to said relationship and at least one of saidcharacteristics of said future part.
 39. A method, as set forth in claim38, wherein the step of establishing said future part costcharacteristics comprises the steps of: establishing at least one costdriver associated with said future part in response to saidrelationship; establishing said future part cost characteristic inresponse to said relationship, and said at least one future part costdriver.
 40. A method as set forth in claim 39, wherein said cost driveris at least one of a supplier, a material type, a weight, a finish type,and a volume.